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@solidangle.bsky.social

Reading through this paper AI adoption is shifting programmer labor from writing code to code reviews, which sounds like a good way to burn out a lot of programmers (and limit the pool of future reviewers), for "statistically insignificant" gains in final software output

We find evidence of a bottleneck from the code review process: The average time to review a pull request increases by 49%, the share of pull requests with changes requested nearly doubles, and the number of comments per pull request increases by 35%. Firms also reallocate labor toward review activities: the share of workers performing code reviews increases by 14%. This bottleneck persists following the adoption of AI code review tools. Although firms increasingly use AI to assist with code review, human reviewers continue to play a central role in the review process.View full-size image

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We find evidence of a bottleneck from the code review process: The average time to review a pull request increases by 49%, the share of pull requests with changes requested nearly

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doubles, and the number of comments per pull request increases by 35%. Firms also reallocate labor toward review activities: the share of workers performing code reviews increases by 14%. This bottleneck persists following the adoption of AI code review tools. Although firms increasingly use AI to assist with code review, human reviewers continue to play a central role in the review process.

Story · 56 postsRead post · Bluesky

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  2. @r.v.cx

    I haven't read this study yet, but having read a LOT of "quantitative software engineering" research...studies almost *never* identify productivity increases. Despite vast, vast increases in engineering productivity over the decades. So maybe temper your enthusiasm for an endorsement of your biases.

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    Story · 56 postsRead post · Bluesky